ArticlePDF Available

TreeGraph 2: combining and visualizing evidence from different phylogenetic analyses. BMC Bioinform 11:7

Abstract

Today it is common to apply multiple potentially conflicting data sources to a given phylogenetic problem. At the same time, several different inference techniques are routinely employed instead of relying on just one. In view of both trends it is becoming increasingly important to be able to efficiently compare different sets of statistical values supporting (or conflicting with) the nodes of a given tree topology, and merging this into a meaningful representation. A tree editor supporting this should also allow for flexible editing operations and be able to produce ready-to-publish figures. We developed TreeGraph 2, a GUI-based graphical editor for phylogenetic trees (available from http://treegraph.bioinfweb.info). It allows automatically combining information from different phylogenetic analyses of a given dataset (or from different subsets of the dataset), and helps to identify and graphically present incongruences. The program features versatile editing and formatting options, such as automatically setting line widths or colors according to the value of any of the unlimited number of variables that can be assigned to each node or branch. These node/branch data can be imported from spread sheets or other trees, be calculated from each other by specified mathematical expressions, filtered, copied from and to other internal variables, be kept invisible or set visible and then be freely formatted (individually or across the whole tree). Beyond typical editing operations such as tree rerooting and ladderizing or moving and collapsing of nodes, whole clades can be copied from other files and be inserted (along with all node/branch data and legends), but can also be manually added and, thus, whole trees can quickly be manually constructed de novo. TreeGraph 2 outputs various graphic formats such as SVG, PDF, or PNG, useful for tree figures in both publications and presentations. TreeGraph 2 is a user-friendly, fully documented application to produce ready-to-publish trees. It can display any number of annotations in several ways, and permits easily importing and combining them. Additionally, a great number of editing- and formatting-operations is available.
BioMed Central
Page 1 of 9
(page number not for citation purposes)
BMC Bioinformatics
Open Access
Software
TreeGraph 2: Combining and visualizing evidence from different
phylogenetic analyses
BenCStöver
1,2 and Kai F Müller*1
Address: 1Institute for Evolution and Biodiversity, University of Münster, Hüfferstraße 1, 48149 Münster, Germany and 2Nees Institute, University
of Bonn, Meckenheimer Allee 170, 53115 Bonn, Germany
Email: Ben C Stöver - stoever@bioinfweb.info; Kai F Müller* - kaimueller@uni-muenster.de
* Corresponding author
Abstract
Background: Today it is common to apply multiple potentially conflicting data sources to a given
phylogenetic problem. At the same time, several different inference techniques are routinely
employed instead of relying on just one. In view of both trends it is becoming increasingly important
to be able to efficiently compare different sets of statistical values supporting (or conflicting with)
the nodes of a given tree topology, and merging this into a meaningful representation. A tree editor
supporting this should also allow for flexible editing operations and be able to produce ready-to-
publish figures.
Results: We developed TreeGraph 2, a GUI-based graphical editor for phylogenetic trees
(available from http://treegraph.bioinfweb.info). It allows automatically combining information from
different phylogenetic analyses of a given dataset (or from different subsets of the dataset), and
helps to identify and graphically present incongruences. The program features versatile editing and
formatting options, such as automatically setting line widths or colors according to the value of any
of the unlimited number of variables that can be assigned to each node or branch. These node/
branch data can be imported from spread sheets or other trees, be calculated from each other by
specified mathematical expressions, filtered, copied from and to other internal variables, be kept
invisible or set visible and then be freely formatted (individually or across the whole tree). Beyond
typical editing operations such as tree rerooting and ladderizing or moving and collapsing of nodes,
whole clades can be copied from other files and be inserted (along with all node/branch data and
legends), but can also be manually added and, thus, whole trees can quickly be manually constructed
de novo. TreeGraph 2 outputs various graphic formats such as SVG, PDF, or PNG, useful for tree
figures in both publications and presentations.
Conclusion: TreeGraph 2 is a user-friendly, fully documented application to produce ready-to-
publish trees. It can display any number of annotations in several ways, and permits easily importing
and combining them. Additionally, a great number of editing- and formatting-operations is available.
Background
It has become standard to apply multiple inference tech-
niques to a given phylogenetic problem. The recent inva-
sion of phylogenetics by Bayesian techniques (e.g., [1]),
the ever improving models and algorithms for tree
searches under maximum likelihood (e.g., [2,3]), and the
Published: 5 January 2010
BMC Bioinformatics 2010, 11:7 doi:10.1186/1471-2105-11-7
Received: 17 July 2009
Accepted: 5 January 2010
This article is available from: http://www.biomedcentral.com/1471-2105/11/7
© 2010 Stöver and Müller; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 2 of 9
(page number not for citation purposes)
continuously growing processor speed helped these previ-
ously computationally very expensive approaches to
become a typical component of most phylogenetic stud-
ies, accompanying the widespread parsimony and dis-
tance-based approaches. At the same time, no single
inference technique has consistently proven to be the sin-
gle best choice. Accordingly, the researcher is well-advised
to explore potential method-specific differential results,
leaving him or her with the difficulty of visualizing these
differences for him- or herself and for the reader. Fre-
quently, differences are restricted to the magnitude of var-
ious measures of statistical support (such as jackknife and
bootstrap proportions, Bayesian posterior probabilities),
rather than being apparent from the topology. In addi-
tion, the frequently reported results from topological tests
(e.g., [4]) or tracing of ancestral character states (e.g., [5])
add further importance to being able to assign a variety of
numbers and graphical labels to tree nodes.
To address those needs, the first version of TreeGraph [6]
had been developed, which strongly simplifies the crea-
tion of the final tree figure by the automatic positioning
and formatting of multiple labels per branch. However,
while one support type could directly be imported from
the phylogeny inference program output, the Newick- and
Nexus [7] format used by these programs precluded the
direct import of more branch labels. For all additional
labels (support values), the laborious work of mapping
them onto the appropriate nodes remained. The cumber-
some drawing part of the publication process was mini-
mized, but it remained the user's responsibility to collect
and position all information that was to be displayed at
the nodes.
We figured that automating this process would be very
useful, particularly so in studies of extensive gene family
datasets that may contain several hundred terminals.
Gene family studies using phylogenetic approaches have
become a major focus with the increasing amount of
available fully sequenced genomes. Typically, gene family
trees suffer from weak support [8-10]. The entailed cau-
tion required when interpreting gene family trees
increases the need for testing alternative inference meth-
ods, alignment methods, data partitions, and varying
treatment of questionable alignment regions.
Similarly, the differential contribution of and potential
conflict among different data partitions is frequently esti-
mated by the differential success of resolution and degree
of statistical support in various parts of the tree contrib-
uted by each partition [11]. This has become particularly
important since multigene analysis are the rule rather
than the exception, a trend further fueled by the growing
availability of complete (organellar) genomes that pro-
vide easy access to a large number of genes that can be
concatenated in large data matrices and then subjected to
phylogenetic analyses, e.g. [12].
These trends call for a tree editor that is able to compare
and ultimately visualize congruent and conflicting evi-
dence from different analyses, while guaranteeing flexible
editing and production of high-quality tree figures for
publications.
Implementation
TreeGraph 2 is written in Java and uses Swing for its
graphical user interface (GUI) as well as the Apache Batik
SVG Toolkit (http://xmlgraphics.apache.org/batik/), Free-
HEP (http://java.freehep.org/), Java Math Expression
Parser (http://sourceforge.net/projects/jep/) and Browser-
Launcher (http://browserlaunch2.sourceforge.net/)
libraries. Besides its GUI, which makes editing and for-
matting very intuitive, the current version 2 adds many
features previously unavailable in the command line pre-
cursor and introduces an XML-based native file format
(XTG).
Results and Discussion
Importing data
TreeGraph 2 can read trees in Newick or Nexus format
(including additional annotations in comments specified
by BEAST [13]) as well as phyloXML tree descriptions [14]
and can furthermore import annotations from text files
generated e.g. with a spreadsheet application. Besides
that, TreeGraph 2 facilitates combining information from
different phylogenetic analyses of a given dataset. This is
particularly useful e.g. in the study of extensive gene fam-
ily datasets with large sets of terminals. The following sec-
tions describe this feature in greater detail.
Mapping statistical support onto congruent nodes
For each branch of a tree opened in TreeGraph 2, the cor-
responding support from other trees can be mapped
whenever the topology defined by the current branch is
present in them. Each of these other trees may represent
the result from a different analytical approach or different
data partition, and support values from these trees are
assigned their own label ID by which they are grouped
and amenable to future formatting or editing operations.
Thus, all support values that stem from a particular analy-
sis can be individually formatted e.g. by their relative posi-
tion on the branch and/or their font and style.
Finding conflicting nodes and mapping contradictory support
In some studies not only the support from different anal-
yses has been mapped onto the branches but also the
strongest support for a contradictory topology was deter-
mined by inspection via eye [15,16].
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 3 of 9
(page number not for citation purposes)
TreeGraph 2 uses the following algorithm automate this
(for a better understanding it should be kept in mind that
each branch splits a tree into exactly two subtrees).
Let tree1 specify the topology onto which contradictory
support from other trees should be mapped (example in
Figure 1a). For a given branch branch1 in tree1, the maxi-
mum support for a conflicting branch branch2 from
another tree tree2 (example in Figure 1b) can be found as
follows.
1. Find the branch2 which defines a subtree subtree2
with the smallest number of terminals that contains
all leafs of a subtree subtree1 defined by branch1.
2. Inside subtree2 find all branches that define a sub-
tree which are on the one hand fully enclosed by
subtree2 and on the other hand contain at least one ter-
minal which is also part of subtree1 as well as at least
one leaf which is not.
3. The highest support value in the set of these
branches is added as a conflicting value onto branch1.
This highest conflicting support value can be distin-
guished from congruent values by user-specified formats,
e.g. brackets, asterisks or different colors (see example in
Figure 1).
Editing and formatting capabilities
The program features versatile editing and formatting
options, such as automatically setting branch widths or
colors according to the value of any of the unlimited
number of variables that can be assigned to each node or
branch.
Editing of node/branch data
Node/branch data imported from spread sheets or other
trees (as described above), can be copied from and to
other internal variables, be kept invisible or set visible and
then be freely formatted (individually or across the whole
tree), filtered according to their values or calculated from
each other using an integrated mathematical expression
parser which can access all node/branch data columns.
Figure 2 shows a screenshot displaying a tree and its cor-
responding data table.
Editing operations
Beyond typical editing operations such as tree rerooting
and ladderizing or moving and collapsing of nodes,
whole clades can be copied or cut out and placed into new
empty files or inserted (along with all node/branch data)
into other trees. Since nodes can also be manually added,
whole trees can quickly be manually constructed starting
from an empty file.
The editing operations are facilitated by versatile additive
selection options that allow selecting many elements in a
tree for subsequent formatting with just a few clicks. Addi-
tionally, every operation applied to an opened tree can be
easily undone or redone using the undo-function.
Searching, replacing and translating tree leaf names
Searching and replacing is possible across all node/branch
data columns (including taxon names and node labels).
Merging support values from different analyses - a simple contrived caseFigure 1
Merging support values from different analyses - a simple contrived case. The tree on the left (a) was first opened in
TreeGraph 2 and defines the topology and optionally a first set of support values. (Alternatively a consensus tree of all analyses
or any user-defined tree could be used here.) Afterwards the annotations from another tree (b) have been added which
resulted in a new group of values (c) supporting (green) or contradicting (red) the initially loaded topology (blue).
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 4 of 9
(page number not for citation purposes)
More restrictive alignment file formats do not allow
lengthy taxon names, so names get truncated. In other
cases, the often clumsy taxon- or lab IDs used during a
study survive up to the final alignment, phylogenetic data-
set and the trees constructed from it until they need to be
adjusted for the final tree to be presented in a paper. Tree-
Graph 2 can be requested to apply a translation table to
use "cleaned" taxon names for the final output. This trans-
lation table can be constructed easily with help of the data
export feature and any text editor or spread sheet program.
Furthermore the lab IDs (old terminal names) can be
saved in a hidden data field to be able to identify the ter-
minals by these lab IDs so that additional support values
could still be added later on.
Formatting document elements
Great flexibility is offered by the application as it allows
free formatting of line- and text-formats of all document
elements like nodes, branches or legends (which mark a
group of terminals). Additionally branches can carry an
unlimited number of textual annotations (text labels) or
icons (icon labels) the color, text style or size of which can
also be freely formatted (see Figure 3). All distance values
in TreeGraph 2 (e.g. line width or text height) are specified
in millimeters or DTP-points (1/72 inch). This feature,
along with the image export function (see below), allows
the user to design trees in exactly the size they should
appear in print or in the exported graphic file. In addition,
TreeGraph 2 offers a feature to proportionally rescale all
elements of a subtree or the whole document.
Example view of the TreeGraph 2 GUI showing taxon counts displayed as branch widthsFigure 2
Example view of the TreeGraph 2 GUI showing taxon counts displayed as branch widths. The taxon counts of all
terminal nodes have been imported from a table (text file) to a hidden node data column. The imported annotations have then
been used as source data to set the terminal branch widths. For each TreeGraph 2 document, one can optionally view the
node/branch data table in the right part of the document window as shown here.
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 5 of 9
(page number not for citation purposes)
Automatically setting line width, text height, and color
TreeGraph 2 allows automatically setting all formats (e.g.
branch widths, branch colors, text colors, text heights,
icon sizes) according to the value of a chosen node/
branch data column. This provides a very intuitive way to
graphically present the relative magnitude of, e.g., certain
types of support or rates assigned to branches (see Figure
2 and 3 for examples).
Different view modes
All editing operations are facilitated by a very convenient
way to zoom in and out, fitting the zoom to the window
Displaying multiple annotations and assigning element formats automaticallyFigure 3
Displaying multiple annotations and assigning element formats automatically. The tree in this contrived example
contains several annotations including ancestral divergence times (node heights; expressed as branch lengths in an ultrametric
tree), DNA substitution rates, posterior clade probabilities as they could have been imported by TreeGraph 2 from, e.g., a tree
file generated with help of TreeAnnotator after a BEAST analysis. As in a typical chronogram view, the age of the nodes (in mil-
lion years ago) is expressed by the scale bar at the bottom. In addition, TreeGraph 2 was asked to automatically assign branch
widths and line colors to illustrate the mean evolutionary rates for each branch, while the accuracy of each rate estimate was
illustrated by a filled rectangular label icon above and an unfilled one below each branch (the branch width extended by the size
of the upper icon describes the highest rate in e.g. a 95% confidence interval and the branch width reduced by the size of the
lower icon describes the lowest rate in the interval). Text labels have been used to show the posterior clade probabilities
(above the branches, bold) and the absolute substitution rates in substitutions per site per billion years (below the branches).
Furthermore, this example tree contains star and cross icon labels that could be used, e.g., to highlight specific character state
transitions (such as orange stars indicating "number to character" shifts (filled) or vice versa (not filled), and blue crosses repre-
senting "upper case to lower case" shifts).
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 6 of 9
(page number not for citation purposes)
size, and a miniature overview (Figure 2) for navigating
large trees.
When applicable (i.e., given that branch length informa-
tion is provided), trees can be displayed as phylogram or
chronogram (Figure 3), with multiple options for adjust-
ing a scale bar (to indicate e.g. time spans in chronograms,
rates in ratograms, or branch lengths in phylograms).
Exporting to graphic formats and printing
TreeGraph 2 outputs various vector and (anti-aliased)
pixel graphic formats. Among these are SVG, PDF, or
PNG, supporting transparent background where this
applies. Using the graphic export function of TreeGraph 2,
the most adequate graphic formats, resolutions, and
image sizes for manuscripts, presentation slides, or web
pages, respectively, can be specified.
Help
An extensive, continuously updated online help system is
available under http://treegraph.bioinfweb.info/Help and
can also be accessed (in a context-dependent manner)
from within the program. Additionally, several video tuto-
rials are offered there to get started with TreeGraph 2 (see
http://treegraph.bioinfweb.info/Help/wiki/Tuto
rial:Main_page).
Comparison to previous software
To date, a variety of tree visualization tools have been
released, among which ATV [17], Dendroscope [18],
FigTree (the tree editor accompanying BEAST), the MEGA
tree explorer [19], Mesquite [20], PhyloWidget [21],
TreeDyn [22] and TreeView [23] may be the most widely
distributed. In spite of their great usefulness for the pur-
poses they have been developed for, none of these soft-
ware packages allows simultaneously visualizing, freely
editing, properly formatting and exporting or printing
trees with heavily annotated nodes (see Figure 4).
Although TreeDyn is able to display multiple annotations
on one node it is not able to automatically position them
in a ready-to-publish way or to combine them from differ-
ent analyses. FigTree is able to read the special Newick
annotations generated by BEAST and therefore can also
store several sets of annotations but only offers a limited
number of ways to display them (like branch lengths or
one textual annotation per branch). In contrast TreeGraph
2 (which is also able to read BEAST annotations) can
show a nearly unlimited number of textual annotations at
a time as well as display data in form of branch widths,
line colors or many other formats.
Besides importing additional annotations from tables
(which TreeDyn also offers), TreeGraph 2 is the only edi-
tor which can combine annotations (e.g. statistical sup-
port from different analysis methods) from different trees
(with the same set of terminals). The information gained
this way has a topological component and can therefore
not simply be obtained from data in a table.
A feature closely related to the ones mentioned above is
the ability to calculate numeric or textual annotations by
mathematical expressions which can reference other
annotations (see above). To date, a similar functionality is
not offered by any other tree editor.
TreeGraph 2 features a multitude of format options which
can be combined to every tree element (e.g. branches,
nodes or labels) independently. As Figure 4 shows, no
other tree editor currently provides functionalities like ele-
ment-specific formats for all types of tree elements in
combination with advanced selection options or collision
free positioning of the whole tree. Moreover, none of the
editors that offer at least some of TreeGraph 2's formatting
options allow the user to precisely determine the print lay-
out. In contrast to most other editors, our program offers
context help buttons (which link to the online help sys-
tem) everywhere in the program, making it very easy for
new users to get started.
It should be noted, however, that TreeGraph 2 has been
optimized as a tree editor for producing high quality tree
figures and not as a viewer for trees with many thousands
of taxa which could never be depicted completely in a
publication or presentation. The latter is a specialty of
software specifically designed for this purpose such as,
e.g., Dendroscope [14] (Figure 4).
Since TreeGraph 2 is written in Java and is able to read and
write all its supported formats directly from and to
streams in would be possible to use it in a web application
either on the server (e.g. with Apache Tomcat) or the cli-
ent site (e.g. as an Java applet or a Java webstart applica-
tion) to display and manipulate trees. As yet, our
application would have to be integrated into such a web
application by its programmer manually and we do not
yet offer a ready-to-use plug-in solution for this. We do,
however, offer a full documentation of our source code
(including its interfaces) to facilitate such a web integra-
tion.
Conclusions
With its easy-to-use graphical user interface and a number
of semi-automatic editing and formatting options, Tree-
Graph 2 is a graphical editor useful in the context of any
phylogenetic study. It is particularly useful where multi-
ple, potentially conflicting trees are being produced,
because its automatic combination of information from
different analyses helps to identify and graphically present
such incongruences. The way in which data can be
imported and then assigned to nodes, manipulated or
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 7 of 9
(page number not for citation purposes)
Figure 4 (see legend on next page)
Software (version)
TreeGraph 2
(2.0.40 beta)
Archaeopteryx (ATV)
(0.954 beta)
Dendroscope
(1.3.1, buil d 4)
FigTree
(1.1.1)
Mega Tree editor
(4, build 402 8)
Mesquite
(2.7.1, build 514)
PhyloWidget
(2009-11-11)
TreeDyn
(198.3)
TreeView
(1.6.6)
Import / Export
Newick IE IE IE I IE I IE I I
Nexus IE IE IE IE IE I IE
phyloXML I IE
Nexus (BEAST package data) I IE
Mapping support from other topolgies (analyses)
܂
Annotation import from table
܂   ܂    ܂
Read trees from databases
 ܂    ܂  
Maximum number of terminals
1
2
13
2
16
2
18
2
14
2
14
2
12
2
14
2
14
2
19
Graphic formats
SVG
܂  ܂ ܂    ܂ 
PDF
܂ ܂ ܂ ܂  ܂ ܂  
PNG
܂ ܂ ܂ ܂    ܂ 
Additional vector formats
܂  ܂ ܂ ܂   ܂ ܂
Additional pixel formats
܂ ܂ ܂ ܂ ܂  ܂ ܂ 
Customizable output resolution
܂        
Editing
Undo function
܂
܂
7
܂
7
Advanced selection options
܂  ܂
Manual tree construction
܂ ܂
܂
Displayable textual annotations per node/branch
8
2 2 1 3 2
8
1
Calculation of annotations
2
܂      
Scaling of branch lengths
܂    ܂ ܂ ܂
Copying, cutting and pasting of all tree elements
3
܂ ܂     ܂
Ladderizing
܂ ܂ ܂ ܂  ܂ ܂
9
܂ ܂
Rerooting
܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂
Collapsing nodes (to polytomy)
܂     ܂ ܂ ܂ ܂
Search
܂ ܂ ܂ ܂   ܂ ܂ 
Replace
4
܂     
Formatting
Collision free positioning of all tree elements
܂     
Line formats by annotations
5
܂   ܂  
Text formats by annotations
5
܂     
Positioning by annotations
5
܂     
Legends for node groups
܂    ܂ 
10
Advanced legend positioning
܂     
Text color
܂  ܂ ܂ ܂ ܂ ܂ 
Text color (element specific)
܂  ܂    ܂ 
Text size
܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂
Text size (element specific)
܂  ܂    ܂ 
Font, text style
܂  ܂  ܂  ܂ ܂
Font, text style (element specific)
܂  ܂    ܂ 
Line color
܂ ܂ ܂ ܂ ܂ ܂
܂
11
Line color (element specific)
܂     
Line width
܂  ܂  ܂ ܂ ܂ ܂
11
Line width (element specific)
܂     
Independent start and end branch width
܂     
Proportional rezising of all elements in a subtree
܂     
Customizable scale bar
܂   ܂ ܂ 
View
Print layout in millimeters or inches
܂     
Editable annotation table
܂     
Rectangular cladogram view
܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂
Rectangular phylogram view
܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂ ܂
Network view
  ܂ ܂ ܂  ܂  ܂
Circular view(s)
  ܂ ܂ ܂ ܂ ܂ ܂ ܂
Hiding of subtrees
 ܂ ܂ ܂ ܂  ܂ ܂ 
Help
Documentation
6
܂ ܂
12
܂ ܂ ܂ ܂ ܂
Context help
܂
܂ ܂
12
Video tutorials
܂
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 8 of 9
(page number not for citation purposes)
even converted to color tones, line diameters or other for-
mats allows for a great flexibility in visualizing any kind of
data associated with different parts of the tree. Together
with the possibility to manually construct new clades or
delete clades and the various graphic output formats sup-
ported, TreeGraph 2 greatly reduces the effort during the
preparation of tree figures for presentations or publica-
tions.
Availability and requirements
Project name: TreeGraph 2
Project home page: http://treegraph.bioinfweb.info/
(including an extensive documentation and a develop-
ment section with Javadocs)
Operating system(s): Platform independent (Java 6 has
to be available)
Programming language: Java
Other requirements: Java Runtime Environment 6.0 (or
higher)
License: GNU General Public License
Restrictions to use by non-academics: none
Authors' contributions
BCS developed TreeGraph 2, wrote the online help and
contributed to the concept of the software and the manu-
script. KFM was responsible for the conception and design
of the software, contributed to its help system, and wrote
the manuscript. Both authors have given final approval of
the version to be published.
Acknowledgements
This work was in part supported by DFG grant MU2875/2 to KFM, since
many of the features were added to the program in response to require-
ments encountered during work in the corresponding DFG project "Car-
nivory in Lamiales - Understanding character evolution, substitution rate
plasticity, and genome miniaturization". Financial support to KFM by the
Young Academy of the North Rhine-Westphalian Academy of Sciences
(Nordrhein-Westfälische Akademie der Wissenschaften und der Künste) is
highly appreciated. Thanks to Mark Simmons, Claude dePamphilis, Dietmar
Quandt, and Jörn Müller for helpful suggestions. Finally we want to thank
the authors of the open source libraries used.
References
1. Holder M, Lewis PO: Phylogeny Estimation: Traditional and
Bayesian Approaches. Nature Reviews Genetics 2003, 4:275-284.
2. Whelan S: Spatial and Temporal Heterogeneity in Nucleotide
Sequence Evolution. Molecular Biology and Evolution 2008,
25:1683-1694.
3. Stamatakis A: RAxML-VI-HPC: maximum likelihood-based
phylogenetic analyses with thousands of taxa and mixed
models. Bioinformatics 2006, 22:2688-2690.
4. Shimodaira H: An approximately unbiased test of phylogenetic
tree selection. Systematic Biology 2002, 51:492-508.
5. Pagel M, Meade A, Barker D: Bayesian Estimation of Ancestral
Character States on Phylogenies. Systematic Biology 2004,
53:673-684.
6. Müller J, Müller K: TreeGraph: automated drawing of complex
tree figures using an extensible tree description format.
Molecular Ecology Notes 2004, 4:786-788.
7. Maddison DR, Swofford DL, Maddison WP: Nexus: An extensible
file format for systematic information. Systematic Biology 1997,
46:590-621.
8. Barakat A, Müller KF, Sáenz de Miera LE: Molecular evolutionary
analysis of the Arabidopsis L7 ribosomal protein gene family.
Gene 2007, 403:143-150.
9. Sampedro J, Lee Y, Carey RE, dePamphilis C, Cosgrove DJ: Use of
genomic history to improve phylogeny and understanding of
births and deaths in a gene family. Plant Journal 2005,
44:409-419.
10. Zahn LM, Leebens-Mack JH, Arrington JM, Hu Y, Landherr LL, dePam-
philis CW, Becker A, Theissen G, Ma H: Conservation and diver-
gence in the AGAMOUS subfamily of MADS-box genes:
evidence of independent sub- and neofunctionalization
events. Evolution & Development 2006, 8:30-45.
11. Müller K, Borsch T, Hilu KW: Phylogenetic utility of rapidly
evolving DNA at high taxonomical levels: contrasting matK,
trnT-F and rbcL in basal angiosperms. Molecular Phylogenetics and
Evolution 2006, 41:99-117.
12. Jansen RK, Cai Z, Daniell H, Raubeson L, DePamphilis CW, Leebens-
Mack J, Müller KF, Guisinger-Bellian M, Haberle RC, Hansen AK, et al.:
Analysis of 81 Genes from 64 Chloroplast Genomes Resolves
Relationships in Angiosperms and Identifies Genome-Scale
Evolutionary Patterns. Proceedings of the National Academy of Sci-
ences of the United States of America 2007, 104:19369-19374.
13. Drummond AJ, Rambaut A: BEAST: Bayesian evolutionary anal-
ysis by sampling trees. BMC Evol Biol 2007, 7:214.
14. Han MV, Zmasek CM: phyloXML: XML for evolutionary biology
and comparative genomics. BMC Bioinformatics 2009, 10:356.
Comparison to other tree editorsFigure 4 (see previous page)
Comparison to other tree editors. I: Import, IE: Im- and export. 1All programs tested with balanced binary trees in New-
ick format. The value listed is the number of terminals of the largest tree that could still be opened in less than two minutes on
an average desktop computer (2.2 GHz AMD Athlon™ XP processor, 1 GB RAM). 2Numerical and textual annotations of
nodes and branches can be calculated by any user defined mathematical expression from the values of other annotations in the
tree. 3Any tree element can be copied to any position in the same or another tree (Programs that can only copy whole trees
or paste subtrees to a new file are not checked in this column.). 4User defined text replacement in node names and all annota-
tions. 5Numerical values of annotations define formatting of tree elements (e.g. color, width, text height). 6Documentation
going beyond the original publication and explaining the different options. 7Only the last edit can be undone. (In contrast, Tree-
Graph 2 stores a whole undo history which can be undone (and redone) to any point.). 8Positioning options for the labels are
not offered. 9Only one direction (not up and down). 10TreeDyn allows labeling a group of nodes with a legend (not automati-
cally positioned), but the label gets lost during edit operations like ladderizing. 11Specific formats for subtrees are possible.
Branches and nodes cannot be formatted independently. 12Only very brief descriptions.
Publish with BioMed Central and every
scientist can read your work free of charge
"BioMed Central will be the most significant development for
disseminating the results of biomedical research in our lifetime."
Sir Paul Nurse, Cancer Research UK
Your research papers will be:
available free of charge to the entire biomedical community
peer reviewed and published immediately upon acceptance
cited in PubMed and archived on PubMed Central
yours — you keep the copyright
Submit your manuscript here:
http://www.biomedcentral.com/info/publishing_adv.asp
BioMedcentral
BMC Bioinformatics 2010, 11:7 http://www.biomedcentral.com/1471-2105/11/7
Page 9 of 9
(page number not for citation purposes)
15. Richardson D, Simmons M, Reddy A: Comprehensive compara-
tive analysis of kinesins in photosynthetic eukaryotes. BMC
Genomics 2006, 7:18.
16. Zhang LB, Simmons MP: Phylogeny and delimitation of the
Celastrales inferred from nuclear and plastid genes. System-
atic Botany 2006, 31:122-137.
17. Zmasek CM, Eddy SR: ATV: display and manipulation of anno-
tated phylogenetic trees. Bioinformatics 2001, 17:383-384.
18. Huson D, Richter D, Rausch C, Dezulian T, Franz M, Rupp R: Den-
droscope: An interactive viewer for large phylogenetic trees.
BMC Bioinformatics 2007, 8:460.
19. Kumar S, Tamura K, Nei M: MEGA3: Integrated software for
Molecular Evolutionary Genetics Analysis and sequence
alignment. Briefings in Bioinformatics 2004, 5:150-163.
20. Maddison WP, Maddison DR: Mesquite: A modular system for
evolutionary analysis. Version 1.0. 2003.
21. Jordan GE, Piel WH: PhyloWidget: web-based visualizations for
the tree of life. Bioinformatics 2008, 24:1641-1642.
22. Chevenet F, Brun C, Banuls A-L, Jacq B, Christen R: TreeDyn:
towards dynamic graphics and annotations for analyses of
trees. BMC Bioinformatics 2006, 7:439.
23. Page RDM: TreeView: An application to display phylogenetic
trees on personal computers. Computer Applications in the Bio-
sciences 1996, 12:357-358.
... Separate phylogenetic analysis was conducted for the nsP4 fragment, the E1 fragment and the full genome sequences of nsP's (ORF1), sP's (ORF2) and concatenated ORF1 and ORF2, respectively. Phylogenetic trees were visualized using TreeGraph2 [26]. Pairwise distance (p-distance) analysis was calculated in MEGA 7 (Molecular Evolutionary Genetics Analysis software) [27] and used to determine percentage identities between different MIDV and SINV strains. ...
Article
Full-text available
Although Old World alphaviruses, Middelburg- (MIDV) and Sindbis virus (SINV), have previously been detected in horses and wildlife with neurologic disease in South Africa, the pathogenesis and clinical presentation of MIDV and SINV infections in animals are not well documented. Clinical samples from horses across South Africa with acute or fatal neurologic and febrile infections submitted between 2014–2018 were investigated. In total, 69/1084 (6.36%) and 11/1084 (1.01%) horses tested positive for MIDV and SINV, respectively, by real-time reverse transcription (RT) PCR. Main signs/outcomes for MIDV (n = 69): 73.91% neurological, 75.36% fever, 28.99% icterus and anorexia, respectively, 8.70% fatalities; SINV (n = 11): 54.54% neurological, 72.73% fever, 36.36% anorexia and 18.18% fatalities. MIDV cases peaked in the late summer/autumn across most South African provinces while SINV cases did not show a clear seasonality and were detected in fewer South African provinces. MIDV could still be detected in blood samples via RT-PCR for up to 71,417 and 21 days after onset of signs in 4 horses respectively, suggesting prolonged replication relative to SINV which could only be detected in the initial sample. Phylogenetic analyses based on partial sequences of the nsP4 (MIDV n = 59 and SINV n = 7) and E1 (MIDV n = 45) genes, as well as full genome sequences (MIDV n = 6), clustered the MIDV and SINV strains from the present study with previously detected strains. MIDV infection appears to be more prevalent in horses than SINV infection based on RT-PCR results, however, prevalence estimates might be different when also considering serological surveillance data.
... The burn-in value was set at 25% of sampled topologies. Trees were imported into the tree editor TreeGraph 2.14.0-771 beta [83] for annotation and layout. In addition to BI inference, Wolbachia phylogeny based on concatenated MLST gene sequences was constructed using maximum likelihood (ML) analysis performed in MEGA X [54]. ...
Article
Full-text available
Philaenus spumarius is a cosmopolitan species that has become a major threat to European agriculture being recognized as the main vector of the introduced plant pathogen Xylella fastidiosa , the agent of the “olive quick decline syndrome”, a disease which is devastating olive orchards in southern Italy. Wolbachia are bacterial symbionts of many insects, frequently as reproductive parasites, sometime by establishing mutualistic relationships, able to spread within host populations. Philaenus spumarius harbors Wolbachia , but the role played by this symbiont is unknown and data on the infection prevalence within host populations are limited. Here, the Wolbachia infection rate was analyzed in relation to the geographic distribution and the genetic diversity of the Italian populations of P . spumarius . Analysis of the COI gene sequences revealed a geographically structured distribution of the three main mitochondrial lineages of P . spumarius . Wolbachia was detected in half of the populations sampled in northern Italy where most individuals belonged to the western-Mediterranean lineage. All populations sampled in southern and central Italy, where the individuals of the eastern-Mediterranean lineage were largely prevalent, were uninfected. Individuals of the north-eastern lineage were found only in populations from the Alps in the northernmost part of Italy, at high altitudes. In this area, Wolbachia infection reached the highest prevalence, with no difference between north-eastern and western-Mediterranean lineage. Analysis of molecular diversity of COI sequences suggested no significant effect of Wolbachia on population genetics of P . spumarius . Using the MLST approach, six new Wolbachia sequence types were identified. Using FISH, Wolbachia were observed within the host’s reproductive tissues and salivary glands. Results obtained led us to discuss the role of Wolbachia in P . spumarius , the factors influencing the geographic distribution of the infection, and the exploitation of Wolbachia for the control of the vector insect to reduce the spread of X . fastidiosa .
... The Markov k model with only variable characters (Mkv = aMino-Keto pairing (MK) + ascertainment bias correction (ASC)) with a gamma distribution (Lewis 2001) was selected for morphological partition. Stöver and Müller 2010). Morphological characters were optimised on the MP tree based on the morphological-only data using WinClada with unambiguous character optimisation and homoplasy mapping by state. ...
... Bootstrap values were calculated with 100 replicates. Phylogenetic trees were arranged in TreeGraph2 (Stöver and Müller 2010), and final editing and annotation used Adobe Illustrator (Adobe Systems Inc., San Jose, California). ...
Article
Full-text available
In March and April 2018, we carried out a survey of myxosporean parasites in coastal fishes collected from Nha Trang Bay in Vietnam’s East Sea. Of the 159 fish specimens, 18 fish species were represented, belonging to 10 families. In 8 host species, 7 myxosporean species were found, representing the genera Kudoa and Unicapsula. Two of these species were new to science: Kudoa igori n. sp. from the gallbladder of Longarm mullet Osteomugil cunnesius (Valenciennes, 1836) (prevalence 10%) and Kudoa borimiri n. sp. from skeletal muscles of Longarm mullet and Longfinned mullet Osteomugil perusii (Valenciennes, 1836) (prevalence 30% and 60%, respectively). Vegetative stages were not found. Spores of K. igori n. sp. were small, orbicular to quadrate in apical view, and with four equal valves. In lateral view, spores were shallowly ovoid with a slightly protruding anterior pole. The 4 polar capsules were slightly unequal sizes and were oriented toward the apex of the spore. Dimensions were as follows: spore length 4.56 ± 0.22 (4.18–4.56), thickness 4.42 ± 0.39 (3.55–5.13), width 5.74 ± 0.46 (4.66–6.50), length of biggest polar capsule 1.38 ± 0.14 (1.1–1.65), middle 1.28 ± 0.12 (1.03–1.53), smallest 1.13 ± 0.11 (0.94–1.30), width of biggest polar capsule 1.03 ± 0.14 (0.83–1.4), middle 0.92 ± 0.12 (0.76–1.08), smallest 0.74 ± 0.12 (0.55–0.94). Spores of K. borimiri n. sp. had four equal valves with slightly rounded ends and were quadrate in apical view. In lateral view, spores were broadly deltoid. Four equal-sized polar capsules opened at the apex of the spore. In O. cunnesius, spore dimensions were as follows: length 3.51 ± 0.15 (3.34–3.92), thickness 3.65 ± 0.38 (2.79–4.21), width 4.97 ± 0.37 (4.13–5.97), length of the polar capsules 1.23 ± 0.18 (0.99–1.57), width 0.88 ± 0.07 (0.70–1.00). Overlapping dimensions for K. borimiri n. sp. spores were also found in O. perusii. Other known myxozoan species we encountered were Kudoa thyrsites and Kudoa whippsi, which had not previously been reported from the East Sea and Vietnam. We also encountered Kudoa monodactyli, which had not previously been reported from Nha Trang Bay. In addition, we report 2 additional species, a Kudoa sp. and a Unicapsula sp., that were not attributable to previously described myxozoans and need further investigation to completely characterize.
Article
Hemipilia yajiangensis, a new orchid species from western Sichuan, China is described and illustrated based on molecular and morphological evidence. It is morphologically similar to H. galeata and H. hemipilioides, but H. yajiangensis is clearly distinguished by its ovate to broadly ovate, deep green with whitish reticulate lined leaf, elliptic dorsal sepal, lanceolate to ligulate lateral lip lobe, as well as obovate and sometimes nearly quadrate midlobe. Phylogenetically, nuclear (nrITS) and plastid (combined matK, psaB, psbA-trnH, rbcL plus trnL-F) trees consistently demonstrate that H. yajiangensis is sister to H. galeata, and support the new species as one of the members of H. sect. Hemipilia as defined by Tang et al.
Article
Full-text available
The genus Liriomyza Mik (Diptera: Agromyzidae) is a diverse and globally distributed group of acalyptrate flies. Phylogenetic relationships among Liriomyza species have remained incompletely investigated and have never been fully addressed using molecular data. Here, we reconstruct the phylogeny of the genus Liriomyza using various phyloge-netic methods (maximum likelihood, Bayesian inference, and gene tree coalescence) on target-capture-based phylogenomic datasets (nucleotides and amino acids) obtained from anchored hybrid enrichment (AHE). We have recovered tree topologies that are nearly congruent across all data types and methods, and individual clade support is strong across all phylogenetic analyses. Moreover, defined morphological species groups and clades are well-supported in our best estimates of the molecular phylogeny. Lirio-myza violivora (Spencer) is a sister group to all remaining sampled Liriomyza species, and the well-known polyphagous vegetable pests [L. huidobrensis (Blanchard), L. langei Frick, L. bryoniae. (Kaltenbach), L. trifolii (Burgess), L. sativae Blanchard, and L. brassicae (Riley)]. belong to multiple clades that are not particularly closely related on the trees. Often, closely related Liriomyza species feed on distantly related host plants. We reject the hypothesis that cophylogenetic processes between Liriomyza species and their host plants drive diversification in this genus. Instead, Liriomyza exhibits a widespread pattern of major host shifts across plant taxa. Our new phylogenetic estimate for Liriomyza species provides considerable new information on the evolution of host-use patterns in this genus. In addition, it provides a framework for further study of the morphology, ecology, and diversification of these important flies. K E Y W O R D S anchored hybrid enrichment, host use, Liriomyza, morphology, phylogeny
Chapter
Alphaproteobacteria is one of the most abundant bacterial lineages that successfully colonize diverse marine and terrestrial environments on Earth. In addition, many alphaproteobacterial lineages have established close association with eukaryotes. This makes Alphaproteobacteria a promising system to test the link between the emergence of ecologically important bacteria and related geological events and the co-evolution between symbiotic bacteria and their hosts. Understanding the timescale of evolution of Alphaproteobacteria is key to testing these hypotheses, which is limited by the scarcity of bacterial fossils, however. Based on the mitochondrial endosymbiosis which posits that the mitochondrion originated from an alphaproteobacterial lineage, we propose a new strategy to estimate the divergence times of lineages within the Alphaproteobacteria by leveraging the fossil records of eukaryotes. In this chapter, we describe the workflow of the mitochondria-based method to date Alphaproteobacteria evolution by detailing the software, methods, and commands used for each step. Visualization of data and results is also described. We also provide related notes with background information and alternative options. All codes used to build this protocol are made available to the public, and we strive to make this protocol user-friendly in particular to microbiologists with limited practical skills in bioinformatics.Key wordsAlphaproteobacteriaRickettsialesMitochondriaMitochondrial endosymbiosisRelaxed molecular clockMolecular dating
Article
Full-text available
Bats harbour a diverse array of viruses, some of which are zoonotic, and are one of the most speciose groups of mammals on earth. As part of an ongoing bat-associated viral diversity research project, we identified three cycloviruses (family Circoviridae) in fecal samples of silver-haired bats (Lasionycteris noctivagans) caught in Cave Creek Canyon of Arizona (USA). Two of the three identified genomes represent two new species in the genus Cyclovirus. Cycloviruses have been found in a wide range of environments and hosts; however, little is known about their biology. These new genomes of cycloviruses are the first from silver-haired bats, adding to the broader knowledge of cyclovirus diversity. With continuing studies, it is likely that additional viruses of the family Circoviridae will be identified in Arizona bat populations.
Article
Full-text available
In a previous study we described a Helitron transposon that apparently became one of the segments in the symbiotic Cotesia vestalis bracovirus (CvBV) from the parasitoid wasp C. vestalis. We presented evidence that this Helitron, named Hel_c35, invaded the C. vestalis genome through a horizontal transfer (HT) event from a dipteran and was later transferred horizontally from C. vestalis to a lepidopteran species. Based on the phylogeny of Hel_c35, we suggested that both HTs occurred in East Asia. We have also anticipated that, as more sequenced genomes from new species become available, more HTs involving Hel_c35 would be detected. Although the inclusion of Hel_c35 as a CvBV segment turned out to be a methodological artifact, the fact that Hel_c35 copies are present in the genomes of C. vestalis and other arthropods still remains. Here, we investigated the evolution of Hel_c35 in arthropods using an updated data set to reassess our previous findings. Most species (95%) included in the present work had their genomes sequenced after our initial study was published, thus representing new descriptions of taxa harboring Hel_c35. Our results expand considerably the number of putative HTs involving Hel_c35, with up to dozens of previously undescribed events, and suggest that the most recent HTs associated with C. vestalis took place in Europe. Considering the phylogenetic distribution of Hel_c35, and the evidence that its DNA sequences are present in the calyx fluid of C. vestalis and tissues from its parasitized host, we argue that many HT events were favored by the behavior of this wasp.
Article
Full-text available
Yeast-insect interactions are compelling models to study the evolution, ecology, and diversification of yeasts. Fungus-growing (attine) ants are prominent insects in the Neotropics that evolved an ancient fungiculture of basidiomycete fungi over 55–65 million years, supplying an environment for a hidden yeast diversity. Here we assessed the yeast diversity in the attine ant environment by thoroughly sampling fungus gardens across four out of five ant fungiculture systems: Acromyrmex coronatus and Mycetomoellerius tucumanus standing for leaf-cutting and higher-attine fungicultures, respectively; Apterostigma sp., Mycetophylax sp., and Mycocepurus goeldii as ants from the lower-attine fungiculture. Among the fungus gardens of all fungus-growing ants examined, we found taxonomically unique and diverse microbial yeast communities across the different fungicultures. Ascomycete yeasts were the core taxa in fungus garden samples, with Saccharomycetales as the most frequent order. The genera Aureobasidium, Candida, Papiliotrema, Starmerella, and Sugiyamaella had the highest incidence in fungus gardens. Despite the expected similarity within the same fungiculture system, colonies of the same ant species differed in community structure. Among Saccharomycotina yeasts, few were distinguishable as killer yeasts, with a classical inhibition pattern for the killer phenotype, differing from earlier observations in this environment, which should be further investigated. Yeast mycobiome in fungus gardens is distinct between colonies of the same fungiculture and each ant colony harbors a distinguished and unique yeast community. Fungus gardens of attine ants are emergent environments to study the diversity and ecology of yeasts associated with insects.
Article
Full-text available
With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.
Article
Full-text available
A phylogenetic analysis of the Celastrales was performed using nuclear (18S, ITS 1, 26S rDNA) and plastid (atpB, matK, rbcL, trnL-F spacer) genes. In contrast to most previous studies, Celastrales and Malpighiales are resolved as being more closely related to one another than either are to Oxalidales. The Huaceae are well supported as the sister group to Oxalidales, not Celastrales, as had been previously proposed. The Lepidobotryaceae are unambiguously supported as sister to the clade consisting of Celastraceae and Parnassiaceae. The Parnassiaceae are well supported as members of an early branching lineage within Celastraceae, rather than as its sister group. Likewise, Pottingeria appears to be part of an early derived lineage of Celastraceae. Empleuridium is unambiguously supported as a derived member of Celastraceae, as are Brexia, Canotia, Siphonodon, Stackhousia, and Tripterococcus. Bhesa is unambiguously supported as a member of Malpighiales, though its relationships within the order remain unclear. Perrottetia should be transferred out of Celastraceae and into eurosids II, being closely related to Tapiscia and Dipentodon. These results help delimit the Celastrales and Celastraceae as morphologically more homogeneous taxa.
Article
Full-text available
A phylogenetic analysis of the Celastrales was performed using nuclear (18S, ITS 1, 26S rDNA) and plastid (atpB, matK, rbcL, trnL-F spacer) genes. In contrast to most previous studies, Celastrales and Malpighiales are resolved as being more closely related to one another than either are to Oxalidales. The Huaceae are well supported as the sister group to Oxalidales, not Celastrales, as had been previously proposed. The Lepidobotryaceae are unambiguously supported as sister to the clade consisting of Celastraceae and Parnassiaceae. The Parnassiaceae are well supported as members of an early branching lineage within Celastraceae, rather than as its sister group. Likewise, Pottingeria appears to be part of an early derived lineage of Celastraceae. Empleuridium is unambiguously supported as a derived member of Celastraceae, as are Brexia, Canotia, Siphonodon, Stackhousia, and Tripterococcus. Bhesa is unambiguously supported as a member of Malpighiales, though its relationships within the order remain unclear. Perrottetia should be transferred out of Celastraceae and into eurosids II, being closely related to Tapiscia and Dipentodon. These results help delimit the Celastrales and Celastraceae as morphologically more homogeneous taxa.
Article
Full-text available
Evolutionary trees are central to a wide range of biological studies. In many of these studies, tree nodes and branches need to be associated (or annotated) with various attributes. For example, in studies concerned with organismal relationships, tree nodes are associated with taxonomic names, whereas tree branches have lengths and oftentimes support values. Gene trees used in comparative genomics or phylogenomics are usually annotated with taxonomic information, genome-related data, such as gene names and functional annotations, as well as events such as gene duplications, speciations, or exon shufflings, combined with information related to the evolutionary tree itself. The data standards currently used for evolutionary trees have limited capacities to incorporate such annotations of different data types. We developed a XML language, named phyloXML, for describing evolutionary trees, as well as various associated data items. PhyloXML provides elements for commonly used items, such as branch lengths, support values, taxonomic names, and gene names and identifiers. By using "property" elements, phyloXML can be adapted to novel and unforeseen use cases. We also developed various software tools for reading, writing, conversion, and visualization of phyloXML formatted data. PhyloXML is an XML language defined by a complete schema in XSD that allows storing and exchanging the structures of evolutionary trees as well as associated data. More information about phyloXML itself, the XSD schema, as well as tools implementing and supporting phyloXML, is available at http://www.phyloxml.org.
Article
Full-text available
A Tree Viewer (ATV) is a Java tool for the display and manipulation of annotated phylogenetic trees. It can be utilized both as a standalone application and as an applet in a web browser. Availability: ATV is available via WWW at http://www.genetics.wustl.edu/eddy/atv/ and via FTP at ftp://ftp.genetics.wustl.edu/pub/eddy/software/forester.tar.Z Contact: eddy@genetics.wustl.edu
Article
PhyloWidget is a web-based tool for the visualization and manipulation of phylogenetic tree data. It can be accessed online or downloaded as a standalone application. A simple URL-based API allows databases to easily link to and customize PhyloWidget for interactively viewing medium-to large-sized trees. Availability: PhyloWidget is available for online use or download at http://www.phylowidget.org/. Its source code is released under the GNU General Public License. Contact: phylowidget@treebase.org
Article
Summary: ATV (A Tree Viewer) is a Java tool for the display and manipulation of annotated phylogenetic trees. It can be utilized both as a standalone application and as an applet in a web browser. Availability: ATV is available via WWW at http://www.genetics.wustl.edu/eddy/atv/ and via FTP at ftp://ftp.genetics.wustl.edu/pub/eddy/software/forester.tar.Z Contact: eddy@genetics.wustl.edu
Article
treegraph assists in producing complex ready-to-publish figures of phylogenetic trees. The TGF format used by the program automates formatting of several different statistical support value types (confidence estimates) per tree node. Moreover, internal text and graphical labels are automatically arranged at the nodes as are annotations for clades or groups of terminals. treegraph imports nexus trees and related file formats. Beyond common tree edit operations, simultaneous pruning of subtrees (simplification of the tree to higher order clades) and saving of subtrees is possible. treegraph exports to the standard vector graphics formats Scalable Vector Graphics and PostScript.